Overview As Global Engineer, Industrial Data Science, you will develop and deploy analytics across Nexteer's global manufacturing operations to turn production, quality, and equipment data into tangible improvements. You collaborate with cross-functional teams to establish scalable data methods, data standards, and reusable analytics for optimization, predictive maintenance, and digital manufacturing initiatives. You will shape global data-driven decisions, support ESP/IIoT platforms, and advance factory intelligence. This is a hands-on role at scale, enabling safer, higher-quality, and more efficient manufacturing.
Responsibilities- Analyze manufacturing and quality data to uncover trends, losses, and improvement opportunities
- Develop descriptive to prescriptive analytics supporting scrap reduction, yield, throughput, and OEE
- Build/validate statistical and ML models for anomaly detection and predictive maintenance
- Create reusable Python analytics workflows and data products for manufacturing applications
- Acquire, clean, transform, and connect data from PLCs, SCADA, MES, traceability, ERP, sensors
- Develop scalable data pipelines and datasets for analysis and deployment
- Collaborate with Automation, IT, OT to improve data governance and cybersecurity compliance
- Support Smart Factory, MES, IIoT, Digital Twin, and industrial AI initiatives
- Develop dashboards and data models using Power BI and Python; define KPI standards
- Lead or support cross-functional analytics projects and coach data literacy in plants
Key requirements- Minimum 5+ years in manufacturing analytics, quality analytics, or related fields
- Proficiency in Python for data prep, analysis, and model development
- Working proficiency with SQL and relational data concepts
- Experience building BI solutions with Power BI and advanced Excel
- Fluent English, strong communication and presentation skills
- Ability to work independently and in global cross-functional teams; willingness to travel
- Track record applying data analysis to manufacturing or operational improvements
- Strong analytical thinking
- Structured problem-solving
- Clear written and verbal communication
- Python for data preparation, analysis, visualization, automation, and modeling
- SQL and relational databases
- Power BI and Excel for analytics and dashboards
